Statically-sized variables (everything except mapping and dynamically-sized array types) are laid out contiguously in storage starting from position 0. Multiple items that need less than 32 bytes are packed into a single storage slot if possible, according to the following rules:

The first item in a storage slot is stored lower-order aligned.

Elementary types use only that many bytes that are necessary to store them.

If an elementary type does not fit the remaining part of a storage slot, it is moved to the next storage slot.

Structs and array data always start a new slot and occupy whole slots (but items inside a struct or array are packed tightly according to these rules).

Warning

When using elements that are smaller than 32 bytes, your contract’s gas usage may be higher.
This is because the EVM operates on 32 bytes at a time. Therefore, if the element is smaller
than that, the EVM must use more operations in order to reduce the size of the element from 32
bytes to the desired size.

It is only beneficial to use reduced-size arguments if you are dealing with storage values
because the compiler will pack multiple elements into one storage slot, and thus, combine
multiple reads or writes into a single operation. When dealing with function arguments or memory
values, there is no inherent benefit because the compiler does not pack these values.

Finally, in order to allow the EVM to optimize for this, ensure that you try to order your
storage variables and struct members such that they can be packed tightly. For example,
declaring your storage variables in the order of uint128,uint128,uint256 instead of
uint128,uint256,uint128, as the former will only take up two slots of storage whereas the
latter will take up three.

The elements of structs and arrays are stored after each other, just as if they were given explicitly.

Due to their unpredictable size, mapping and dynamically-sized array types use a Keccak-256 hash
computation to find the starting position of the value or the array data. These starting positions are always full stack slots.

The mapping or the dynamic array itself
occupies an (unfilled) slot in storage at some position p according to the above rule (or by
recursively applying this rule for mappings to mappings or arrays of arrays). For a dynamic array, this slot stores the number of elements in the array (byte arrays and strings are an exception here, see below). For a mapping, the slot is unused (but it is needed so that two equal mappings after each other will use a different hash distribution).
Array data is located at keccak256(p) and the value corresponding to a mapping key
k is located at keccak256(k.p) where . is concatenation. If the value is again a
non-elementary type, the positions are found by adding an offset of keccak256(k.p).

bytes and string store their data in the same slot where also the length is stored if they are short. In particular: If the data is at most 31 bytes long, it is stored in the higher-order bytes (left aligned) and the lowest-order byte stores length*2. If it is longer, the main slot stores length*2+1 and the data is stored as usual in keccak256(slot).

Scratch space can be used between statements (ie. within inline assembly).

Solidity always places new objects at the free memory pointer and memory is never freed (this might change in the future).

Warning

There are some operations in Solidity that need a temporary memory area larger than 64 bytes and therefore will not fit into the scratch space. They will be placed where the free memory points to, but given their short lifecycle, the pointer is not updated. The memory may or may not be zeroed out. Because of this, one shouldn’t expect the free memory to be zeroed out.

When a Solidity contract is deployed and when it is called from an
account, the input data is assumed to be in the format in the ABI
specification. The ABI specification requires arguments to be padded to multiples of 32
bytes. The internal function calls use a different convention.

When a value is shorter than 256-bit, in some cases the remaining bits
must be cleaned.
The Solidity compiler is designed to clean such remaining bits before any operations
that might be adversely affected by the potential garbage in the remaining bits.
For example, before writing a value to the memory, the remaining bits need
to be cleared because the memory contents can be used for computing
hashes or sent as the data of a message call. Similarly, before
storing a value in the storage, the remaining bits need to be cleaned
because otherwise the garbled value can be observed.

On the other hand, we do not clean the bits if the immediately
following operation is not affected. For instance, since any non-zero
value is considered true by JUMPI instruction, we do not clean
the boolean values before they are used as the condition for
JUMPI.

In addition to the design principle above, the Solidity compiler
cleans input data when it is loaded onto the stack.

The Solidity optimizer operates on assembly, so it can be and also is used by other languages. It splits the sequence of instructions into basic blocks at JUMPs and JUMPDESTs. Inside these blocks, the instructions are analysed and every modification to the stack, to memory or storage is recorded as an expression which consists of an instruction and a list of arguments which are essentially pointers to other expressions. The main idea is now to find expressions that are always equal (on every input) and combine them into an expression class. The optimizer first tries to find each new expression in a list of already known expressions. If this does not work, the expression is simplified according to rules like constant+constant=sum_of_constants or X*1=X. Since this is done recursively, we can also apply the latter rule if the second factor is a more complex expression where we know that it will always evaluate to one. Modifications to storage and memory locations have to erase knowledge about storage and memory locations which are not known to be different: If we first write to location x and then to location y and both are input variables, the second could overwrite the first, so we actually do not know what is stored at x after we wrote to y. On the other hand, if a simplification of the expression x - y evaluates to a non-zero constant, we know that we can keep our knowledge about what is stored at x.

At the end of this process, we know which expressions have to be on the stack in the end and have a list of modifications to memory and storage. This information is stored together with the basic blocks and is used to link them. Furthermore, knowledge about the stack, storage and memory configuration is forwarded to the next block(s). If we know the targets of all JUMP and JUMPI instructions, we can build a complete control flow graph of the program. If there is only one target we do not know (this can happen as in principle, jump targets can be computed from inputs), we have to erase all knowledge about the input state of a block as it can be the target of the unknown JUMP. If a JUMPI is found whose condition evaluates to a constant, it is transformed to an unconditional jump.

As the last step, the code in each block is completely re-generated. A dependency graph is created from the expressions on the stack at the end of the block and every operation that is not part of this graph is essentially dropped. Now code is generated that applies the modifications to memory and storage in the order they were made in the original code (dropping modifications which were found not to be needed) and finally, generates all values that are required to be on the stack in the correct place.

These steps are applied to each basic block and the newly generated code is used as replacement if it is smaller. If a basic block is split at a JUMPI and during the analysis, the condition evaluates to a constant, the JUMPI is replaced depending on the value of the constant, and thus code like

As part of the AST output, the compiler provides the range of the source
code that is represented by the respective node in the AST. This can be
used for various purposes ranging from static analysis tools that report
errors based on the AST and debugging tools that highlight local variables
and their uses.

Furthermore, the compiler can also generate a mapping from the bytecode
to the range in the source code that generated the instruction. This is again
important for static analysis tools that operate on bytecode level and
for displaying the current position in the source code inside a debugger
or for breakpoint handling.

Both kinds of source mappings use integer indentifiers to refer to source files.
These are regular array indices into a list of source files usually called
"sourceList", which is part of the combined-json and the output of
the json / npm compiler.

The source mappings inside the AST use the following
notation:

s:l:f

Where s is the byte-offset to the start of the range in the source file,
l is the length of the source range in bytes and f is the source
index mentioned above.

The encoding in the source mapping for the bytecode is more complicated:
It is a list of s:l:f:j separated by ;. Each of these
elements corresponds to an instruction, i.e. you cannot use the byte offset
but have to use the instruction offset (push instructions are longer than a single byte).
The fields s, l and f are as above and j can be either
i, o or - signifying whether a jump instruction goes into a
function, returns from a function or is a regular jump as part of e.g. a loop.

In order to compress these source mappings especially for bytecode, the
following rules are used:

If a field is empty, the value of the preceding element is used.

If a : is missing, all following fields are considered empty.

This means the following source mappings represent the same information:

Use shorter types for struct elements and sort them such that short types are grouped together. This can lower the gas costs as multiple SSTORE operations might be combined into a single (SSTORE costs 5000 or 20000 gas, so this is what you want to optimise). Use the gas price estimator (with optimiser enabled) to check!

Make your state variables public - the compiler will create getters for you automatically.

If you end up checking conditions on input or state a lot at the beginning of your functions, try using Function Modifiers.

If your contract has a function called send but you want to use the built-in send-function, use address(contractVariable).send(amount).

Initialise storage structs with a single assignment: x=MyStruct({a:1,b:2});